Yunhao (Andy) Ge

葛云皓

CS Ph.D. Candidate @ University of Southern California

Visiting Ph.D. Student @ Stanford University

Amazon Fellow with Amazon ML Fellowship (2022-2023)

Email: yunhaoge at usc dot edu; yunhaoge at stanford dot edu

    [About Me] [News & Updates] [Publications] [Experience]


About Me

                                             

I am a Ph.D. Candidate in the CS Department at University of Southern California, advised by Prof. Laurent Itti. I am also a Visiting PhD Student at Stanford Vision and Learning Lab (SVL) advised by Prof. Jiajun Wu. I'm interested in how could human efficiently teach AI to learn the human ability to perceive, understand, interact, and reason the physical world. My current research focuses include:

I also work closely with Dr. Vibhav Vineet (Microsoft Research), Dr. Jie Ren (Google Brain), Dr. Jiaping Zhao (Google Research), and Dr. Ziyan Wu (UII America). Previously, I was fortunate to intern/work at Google Research, Google Cloud AI, Microsoft Research, United Imaging Intelligence, and Flexiv Robotics.

Before that, I got my M.Sc. degree at Robotics Institute at Shanghai Jiao Tong University, and B.Eng. degree of Mechatronics at Shandong University.

Research opportunities: I am happy to collaboration. If you are interested, please send me an email. I especially encourage USC master/undergraduate students who want to involve exciting projects targeting top-tier conferences/journals to reach out.


News & Updates


Preprints

        
Building One-class Detector for Anything: Open-vocabulary Zero-shot OOD Detection Using Text-image Models

Yunhao Ge*, Jie Ren*, Jiaping Zhao, Kaifeng Chen, Andrew Gallagher, Laurent Itti, and Balaji Lakshminarayanan (*=equal contribution)
arXiv:2305.17207, 2023.

[paper]

DALL-E for Detection: Language-driven Compositional Image Synthesis for Object Detection

Yunhao Ge*, Jiashu Xu*, Brian Nlong Zhao, Laurent Itti, Vibhav Vineet (*=equal contribution)
arXiv:2206.09592, 2022.

[paper]

EM-Paste: EM-guided Cut-Paste with DALL-E Augmentation for Image-level Weakly Supervised Instance Segmentation

Yunhao Ge*, Jiashu Xu*, Brian Nlong Zhao, Laurent Itti, Vibhav Vineet (*=equal contribution)
arXiv:2212.07629, 2022.

[paper]

Selected Publications [Google Scholar]

                                
Lightweight Learner for Shared Knowledge Lifelong Learning

Yunhao Ge, Yuecheng Li, Di Wu, Ao Xu, Adam M. Jones, Amanda Sofie Rios, Iordanis Fostiropoulos, Shixian wen, Po-Hsuan Huang, Zachary William Murdock, Gozde Sahin, Shuo Ni, Kiran Lekkala, Sumedh Anand Sontakke, Laurent Itti
TMLR (Transactions on Machine Learning Research).

[paper] [code]

Improving Zero-shot Generalization and Robustness of Multi-modal Models

Yunhao Ge*, Jie Ren*, Yuxiao Wang, Andrew Gallagher, Ming-Hsuan Yang, Laurent Itti, Hartwig Adam, Balaji Lakshminarayanan, and Jiaping Zhao (*=equal contribution)
CVPR 2023 (IEEE/ CVF International Conference on Computer Vision and Pattern Recognition).

[paper]

Neural-Sim: Learning to Generate Training Data with NeRF

Yunhao Ge, Harkirat Behl*, Jiashu Xu*, Suriya Gunasekar, Neel Joshi, Yale Song, Xin Wang, Laurent Itti, and Vibhav Vineet (*=equal contribution as second author)
ECCV 2022 (European Conference on Computer Vision).

[paper] [code]

Contributions of Shape, Texture, and Color in Visual Recognition

Yunhao Ge*, Yao Xiao*, Zhi Xu, Xingrui Wang, Laurent Itti (*=equal contribution)
ECCV 2022 (European Conference on Computer Vision).

[paper] [code]

A Peek Into the Reasoning of Neural Networks: Interpreting with Structural Visual Concepts

Yunhao Ge, Yao Xiao, Zhi Xu, Meng Zheng, Srikrishna Karanam, Terrence Chen, Laurent Itti and Ziyan Wu
CVPR 2021 (IEEE/ CVF International Conference on Computer Vision and Pattern Recognition).

[paper] [github] [website] [video] [知乎] [机器之心] [AI科技评论]

Zero-shot Synthesis with Group-Supervised Learning

Yunhao Ge, Sami Abu-El-Haija, Gan Xin and Laurent Itti
ICLR 2021 (International Conference on Learning Representations).

[paper] [code] [website] [Fonts Dataset] [USC Viterbi Press] [知乎] [AI科技评论]
[ USC News ] [ Tech Xplore ] [ Technology Networks ]

Invariant Structure Learning for Better Generalization and Causal Explainability

Yunhao Ge, Sercan Ö. Arik, Jinsung Yoon, Ao Xu, Laurent Itti and Tomas Pfister
arXiv:2206.06469, 2022.

[paper]

Encouraging Disentangled and Convex Representation with Controllable Interpolation Regularization

Yunhao Ge, Zhi Xu, Yao Xiao, Gan Xin, Yunkui Pang and Laurent Itti
WACV 2023 (IEEE/CVF Winter Conference on Applications of Computer Vision).

[paper]

Graph Autoencoder for Graph Compression and Representation Learning

Yunhao Ge*, Yunkui Pang*, Linwei Li and Laurent Itti (*=equal contribution)
ICLR 2021 Workshop (Neural Compression: From Information Theory to Applications--Workshop@ ).

[paper] [code] [Img2SceneGraph]

Spotlight Presentation

Pose Augmentation: Class-agnostic Object Pose Transformation for Object Recognition

Yunhao Ge, Jiaping Zhao, Laurent Itti
ECCV 2020 (European Conference on Computer Vision).

[paper] [github] [video-1min] [video-10min]

Beneficial Perturbation Network for designing general adaptive artificial intelligence systems

Shixian Wen, Amanda Rios*, Yunhao Ge* and Laurent Itti (*=equal contribution as second author)
TNNLS 2021 ( IEEE Transactions on Neural Networks and Learning Systems ).

[paper]

Unpaired MR to CT Synthesis with Explicit Structural Constrained Adversarial Learning

Yunhao Ge*, Dongming Wei*, Zhong Xue, Yiqiang Zhan, Xiang Zhou, Qian Wang and Shu Liao (*=equal contribution)
ISBI 2019 (IEEE International Symposium on Biomedical Imaging).

[paper] [code]

Synthesis and inpainting-based MR-CT registration for image-guided thermal ablation of liver tumors

Dongming Wei, Sahar Ahmad, Jiayu Huo, Wen Peng, Yunhao Ge, Zhong Xue, Pew-Thian Yap, Wentao Li, Dinggang Shen, Qian Wang
MICCAI 2019 (International Conference on Medical Image Computing and Computer-Assisted Intervention).

[paper]

Unpaired Whole-body MR to CT Synthesis with Correlation Coefficient Constrained Adversarial Learning

Yunhao Ge, Zhong Xue, Yiqiang Zhan, Xiang Zhou and Shu Liao
SPIE 2019 (SPIE-Medical Imaging).

[paper] [code]

Oral Presentation


Intern & Work Experience

Google Research, Los Angeles, USA (May. 2022 - Dec. 2022)

Google Cloud AI, Mountain View, USA (Aug. 2021 - May 2022)

Microsoft Research, Redmond, USA (May. 2021 - Aug. 2021)

UII America, Inc, Boston, USA (May. 2020 - Aug. 2020)

Flexiv Ltd, Shanghai, China (May. 2019 - Aug. 2019)

United Imaging Intelligence Co., Ltd, Shanghai, China (Jun. 2018 - Apr. 2019)


Scholarships


Honors and Awards


Academic Service

Reviewer of the following conferences/journals:

NeurIPS 2023, 2022, 2021
CVPR 2023, 2022
ECCV 2022
ICCV 2023, 2021
ICLR 2023, 2022
ICML 2022
WACV 2023
IEEE Transactions on Medical Imaging (TMI)
IEEE Access
Applied Optics

Software & Patents

Systems and methods for image processing
S Liao, GE Yunhao, WEI Dongming
US Patent App. 16/729,303.

Pulmonary Nodular Assisted Detection System Based on AI(V1.0)
Bin Li, Yunhao Ge
2018SR037095.

A Two-Layer Barrier Free Parking Equipment Based on Bionic Manipulator
Yunhao Ge, Shangze Yang, Zheng Zhang, Weixin Yan and Yanzheng Zhao
CN201610712048.

A Double Decker Parking Equipment based on Shear Lifting Mechanism and Hydraulic Mechanism
Yunhao Ge, Xulong Zhou, Peng Liu and Yanzheng Zhao
CN201610704408.



Last update: May 10, 2023